The Senior Data Scientist will develop AI/ML solutions, manage data pipelines, optimize healthcare outcomes, and lead projects in NLP and LLMs within a collaborative team.
Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
About Us: At Optum AI, we leverage data and resources to make a significant impact on the healthcare system. Our solutions have the potential to improve healthcare for everyone. We work on cutting-edge projects involving ML, NLP, and LLM techniques, continuously developing and improving generative AI methods for structured and unstructured healthcare data. Our team collaborates with world-class experts and top universities to develop innovative AI/ML solutions, often leading to patents and published papers.
Primary Responsibilities:
5-7+ Years of experience on Gen AI/Agentic AI, NLP, LLMs
This role is responsible for architecting, designing, and delivering end-to-end Generative AI solutions aligned with enterprise business objectives and technology strategy. The position focuses on building scalable, secure, and production ready GenAI architectures using platforms such as Azure OpenAI, HuggingFace, and Databricks, and seamlessly integrating Generative AI capabilities into enterprise applications, data platforms, APIs, and business workflows. The role also involves designing and orchestrating multiagent architectures to enable complex, autonomous, end-to-end AI-driven workflows that deliver measurable business impact.
• Architect, containerize, and deploy LLM applications in cloud environments using Docker, Podman, and Kubernetes following enterprise MLOps standards.
• Apply deep expertise in LLMs, RAG architectures, vector databases, MCP servers, and multiagent frameworks to deliver reliable and context aware GenAI solutions.
• Build intelligent document processing solutions using OCR technologies such as Azure Form Recognizer, Document Intelligence, Tesseract, and computer vision methods.
• Analyze complex technical issues end to end, identify root causes, and implement scalable, long term corrective solutions.
• Build and operate cloud native GenAI platforms within Azure environments while adhering to enterprise architectural, governance, and compliance standards.
• Design and deploy end-to-end data pipelines, machine learning models, and GenAI applications using Azure, Databricks, and Azure Machine Learning.
• Ensure consistent and reliable AI delivery by designing, building, and maintaining CI/CD pipelines for GenAI and ML workloads.
• Demonstrate hands-on expertise in containerization and orchestration using Docker and Podman.
• Apply software monitoring, scalability strategies, and quality management (QMS) practices to maintain high system reliability.
• Leverage DevOps toolchains including GitHub, GitHub Actions, Azure DevOps, and Kubernetes to enable efficient development and deployment workflows.
• Implement security best practices and vulnerability management across AI models, applications, and infrastructure layers.
• Share domain and technical expertise through mentorship, peer collaboration, and cross training to strengthen team capabilities
Required Qualifications:
• Bachelor's degree or higher in Computer Science, Engineering, or a related field, with a focus on Artificial Intelligence, Generative AI, NLP, or Language Processing
• LLMs, Azure OpenAI, Prompt engineering, Embeddings, Azure Document Intelligence, Retrieval Augmented Generation (RAG), LLM evaluation, Hallucination mitigation, Multiagent frameworks, agent orchestration, autonomous agents, workflow coordination, planner-executor patterns, complex AI workflow design
• Hands on experience with LangChain, LlamaIndex, Hugging Face Transformers, LangGraph, CrewAI, and AutoGen
• Root cause analysis, system design trade offs, optimization for cost, performance, and scalability.
• Experience building NLP and LLM powered solutions for text classification, entity extraction (NER), semantic search, summarization, and question answering in enterprise applications
• AI security best practices, vulnerability management, access control, compliance, responsible AI governance
• Familiarity with UI tools like Streamlit, Chainlit, and API Frameworks like Flask, FAST APIs, Rest APIs, REACT etc
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
#NJP
About Us: At Optum AI, we leverage data and resources to make a significant impact on the healthcare system. Our solutions have the potential to improve healthcare for everyone. We work on cutting-edge projects involving ML, NLP, and LLM techniques, continuously developing and improving generative AI methods for structured and unstructured healthcare data. Our team collaborates with world-class experts and top universities to develop innovative AI/ML solutions, often leading to patents and published papers.
Primary Responsibilities:
5-7+ Years of experience on Gen AI/Agentic AI, NLP, LLMs
This role is responsible for architecting, designing, and delivering end-to-end Generative AI solutions aligned with enterprise business objectives and technology strategy. The position focuses on building scalable, secure, and production ready GenAI architectures using platforms such as Azure OpenAI, HuggingFace, and Databricks, and seamlessly integrating Generative AI capabilities into enterprise applications, data platforms, APIs, and business workflows. The role also involves designing and orchestrating multiagent architectures to enable complex, autonomous, end-to-end AI-driven workflows that deliver measurable business impact.
• Architect, containerize, and deploy LLM applications in cloud environments using Docker, Podman, and Kubernetes following enterprise MLOps standards.
• Apply deep expertise in LLMs, RAG architectures, vector databases, MCP servers, and multiagent frameworks to deliver reliable and context aware GenAI solutions.
• Build intelligent document processing solutions using OCR technologies such as Azure Form Recognizer, Document Intelligence, Tesseract, and computer vision methods.
• Analyze complex technical issues end to end, identify root causes, and implement scalable, long term corrective solutions.
• Build and operate cloud native GenAI platforms within Azure environments while adhering to enterprise architectural, governance, and compliance standards.
• Design and deploy end-to-end data pipelines, machine learning models, and GenAI applications using Azure, Databricks, and Azure Machine Learning.
• Ensure consistent and reliable AI delivery by designing, building, and maintaining CI/CD pipelines for GenAI and ML workloads.
• Demonstrate hands-on expertise in containerization and orchestration using Docker and Podman.
• Apply software monitoring, scalability strategies, and quality management (QMS) practices to maintain high system reliability.
• Leverage DevOps toolchains including GitHub, GitHub Actions, Azure DevOps, and Kubernetes to enable efficient development and deployment workflows.
• Implement security best practices and vulnerability management across AI models, applications, and infrastructure layers.
• Share domain and technical expertise through mentorship, peer collaboration, and cross training to strengthen team capabilities
Required Qualifications:
• Bachelor's degree or higher in Computer Science, Engineering, or a related field, with a focus on Artificial Intelligence, Generative AI, NLP, or Language Processing
• LLMs, Azure OpenAI, Prompt engineering, Embeddings, Azure Document Intelligence, Retrieval Augmented Generation (RAG), LLM evaluation, Hallucination mitigation, Multiagent frameworks, agent orchestration, autonomous agents, workflow coordination, planner-executor patterns, complex AI workflow design
• Hands on experience with LangChain, LlamaIndex, Hugging Face Transformers, LangGraph, CrewAI, and AutoGen
• Root cause analysis, system design trade offs, optimization for cost, performance, and scalability.
• Experience building NLP and LLM powered solutions for text classification, entity extraction (NER), semantic search, summarization, and question answering in enterprise applications
• AI security best practices, vulnerability management, access control, compliance, responsible AI governance
• Familiarity with UI tools like Streamlit, Chainlit, and API Frameworks like Flask, FAST APIs, Rest APIs, REACT etc
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
#NJP
Top Skills
Amazon Textract
Aws Sagemaker
Azure
Azure Form Recognizer
Azure Openai
Docker
Fast Apis
Flask
Keras
Kubernetes
Mlflow
Podman
Pyspark
Python
PyTorch
R
Rest Apis
Scala
Scikit-Learn
Streamlit
TensorFlow
Tesseract
Vertex Ai
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